Christopher Henry, PhD
Computational Neuroscientist
Artificial Intelligence Researcher
and Data Scientist
I seek to understand and influence how we interface with the world:
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How do we build efficient, robust neural representations?
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How are they updated amid changing environments and task demands?
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How do we draw inferences from them to guide decisions and behavior?
​To date, my research has focused on how this happens in the human and primate visual system, which is arguably the most highly evolved, flexible, and robust neural network architecture we know of. Using rigorous experimental and computational modeling approaches, I identify system-level principles of neural organization that facilitate our perception, cognition, and behavioral-interaction with the world.
Research Interests
artificial intelligence | machine learning | recurrent and deep neural networks | computer vision
perception | adaptive coding | decision-making | inference and learning | generalization across contexts